In model-based segmentation for computed tomography (CT) images, it is assumed that an organ to be segmented generally has the same image appearance. For each triangle of a surface model, a boundary detection feature that describes the local image appearance is learned. For ultrasound images, image appearance changes when the relative position or orientation of the object to the probe changes. For some applications, it is possible to define the orientation in an acquisition protocol (for example, in Transthoracic Echocardiograms (TTE)) but for other protocols, it is not possible to define the orientation. This is particularly relevant for fetal ultrasound images. As the fetus is moving freely in the uterus, it is impossible to impose that the image be acquired from a fixed orientation with respect to the fetus. Performing adaptation with an incorrect set of features can cause inaccuracies in the segmentation.